Troy won the Brickell Key award for his pioneering work in applying Monte Carlo simulation to forecasting delivery dates. His KanbanSim system takes much of the guesswork out of forecasting, and instead computes both the expected delivery date and its probability distributions, even in situations with complex dependencies and risks. Sure, on average you’ll hit a particular date, but wouldn’t you prefer to know you will make the date with 95% or 99.7% likelihood? Troy may start laughing and tell you that you’re assuming date distributions are Normal, while we should really be using the Weibull distribution.
If you’re like the rest of us, you’ll say, “OK, Troy, if it’s a Weibull distribution, as you say, what date can we hit with roughly 99% certainty?” Troy will stick this question into his Monte Carlo simulator and tell us. And he’ll also tell us how we might change the requirements or address looming risks to bring the date earlier.
We are grateful to be working with Troy, and celebrate his pioneering work. If you need help with more accurate forecasting—whether using Kanban, Scrum or waterfall—give us a shout.